{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,11,15]],"date-time":"2024-11-15T05:19:57Z","timestamp":1731647997704,"version":"3.28.0"},"publisher-location":"Cham","reference-count":33,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031550140"},{"type":"electronic","value":"9783031550157"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024]]},"DOI":"10.1007\/978-3-031-55015-7_3","type":"book-chapter","created":{"date-parts":[[2024,3,13]],"date-time":"2024-03-13T20:57:33Z","timestamp":1710363453000},"page":"29-41","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["RoboNLU: Advancing Command Understanding with\u00a0a\u00a0Novel Lightweight BERT-Based Approach for\u00a0Service Robotics"],"prefix":"10.1007","author":[{"given":"Sinuo","family":"Wang","sequence":"first","affiliation":[]},{"given":"Ma\u00eblic","family":"Neau","sequence":"additional","affiliation":[]},{"given":"C\u00e9dric","family":"Buche","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,3,14]]},"reference":[{"key":"3_CR1","unstructured":"Bastianelli, E., Croce, D., Vanzo, A., Basili, R., Nardi, D., et al.: A discriminative approach to grounded spoken language understanding in interactive robotics. In: IJCAI, pp. 2747\u20132753 (2016)"},{"key":"3_CR2","doi-asserted-by":"crossref","unstructured":"Cai, F., Zhou, W., Mi, F., Faltings, B.: SLIM: explicit slot-intent mapping with BERT for joint multi-intent detection and slot filling. In: ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 7607\u20137611. IEEE (2022)","DOI":"10.1109\/ICASSP43922.2022.9747477"},{"key":"3_CR3","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"130","DOI":"10.1007\/978-3-319-18615-3_11","volume-title":"RoboCup 2014: Robot World Cup XVIII","author":"K Chen","year":"2015","unstructured":"Chen, K., Lu, D., Chen, Y., Tang, K., Wang, N., Chen, X.: The intelligent techniques in robot KeJia \u2013 the champion of RoboCup@Home 2014. In: Bianchi, R.A.C., Akin, H.L., Ramamoorthy, S., Sugiura, K. (eds.) RoboCup 2014. LNCS (LNAI), vol. 8992, pp. 130\u2013141. Springer, Cham (2015). https:\/\/doi.org\/10.1007\/978-3-319-18615-3_11"},{"key":"3_CR4","unstructured":"Chen, Q., Zhuo, Z., Wang, W.: BERT for joint intent classification and slot filling. arXiv preprint arXiv:1902.10909 (2019)"},{"key":"3_CR5","unstructured":"Costello, C., Lin, R., Mruthyunjaya, V., Bolla, B., Jankowski, C.: Multi-layer ensembling techniques for multilingual intent classification (2018)"},{"key":"3_CR6","unstructured":"ONNX Runtime developers: ONNX runtime. https:\/\/onnxruntime.ai\/ (2021). Version: x.y.z"},{"key":"3_CR7","unstructured":"Devlin, J., Chang, M.W., Lee, K., Toutanova, K.: BERT: pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805 (2018)"},{"key":"3_CR8","doi-asserted-by":"crossref","unstructured":"Dowding, J., et al.: GEMINI: a natural language system for spoken-language understanding. arXiv preprint cmp-lg\/9407007 (1994)","DOI":"10.3115\/1075671.1075680"},{"key":"3_CR9","doi-asserted-by":"crossref","unstructured":"Dzifcak, J., Scheutz, M., Baral, C., Schermerhorn, P.: What to do and how to do it: translating natural language directives into temporal and dynamic logic representation for goal management and action execution. In: 2009 IEEE International Conference on Robotics and Automation, pp. 4163\u20134168. IEEE (2009)","DOI":"10.1109\/ROBOT.2009.5152776"},{"key":"3_CR10","doi-asserted-by":"crossref","unstructured":"Eppe, M., Trott, S., Raghuram, V., Feldman, J.A., Janin, A.: Application-independent and integration-friendly natural language understanding. In: GCAI, pp. 340\u2013352 (2016)","DOI":"10.29007\/npsn"},{"key":"3_CR11","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"647","DOI":"10.1007\/978-3-030-04212-7_57","volume-title":"Neural Information Processing","author":"M Firdaus","year":"2018","unstructured":"Firdaus, M., Bhatnagar, S., Ekbal, A., Bhattacharyya, P.: A deep learning based multi-task ensemble model for intent detection and slot filling in spoken language understanding. In: Cheng, L., Leung, A.C.S., Ozawa, S. (eds.) ICONIP 2018. LNCS, vol. 11304, pp. 647\u2013658. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-030-04212-7_57"},{"key":"3_CR12","doi-asserted-by":"crossref","unstructured":"Gangadharaiah, R., Narayanaswamy, B.: Joint multiple intent detection and slot labeling for goal-oriented dialog. In: Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers), pp. 564\u2013569 (2019)","DOI":"10.18653\/v1\/N19-1055"},{"key":"3_CR13","doi-asserted-by":"crossref","unstructured":"Goo, C.W., et al.: Slot-gated modeling for joint slot filling and intent prediction. In: Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers), pp. 753\u2013757 (2018)","DOI":"10.18653\/v1\/N18-2118"},{"key":"3_CR14","doi-asserted-by":"publisher","unstructured":"Guo, D., Tur, G., Yih, W.T., Zweig, G.: Joint semantic utterance classification and slot filling with recursive neural networks. In: 2014 IEEE Spoken Language Technology Workshop (SLT), pp. 554\u2013559 (2014). https:\/\/doi.org\/10.1109\/SLT.2014.7078634","DOI":"10.1109\/SLT.2014.7078634"},{"key":"3_CR15","doi-asserted-by":"crossref","unstructured":"Haffner, P., Tur, G., Wright, J.H.: Optimizing SVMs for complex call classification. In: 2003 Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2003), vol. 1, p. I-I. IEEE (2003)","DOI":"10.1109\/ICASSP.2003.1198860"},{"key":"3_CR16","unstructured":"Hromei, C.D., Croce, D., Basili, R.: Grounding end-to-end architectures for semantic role labeling in human robot interaction. In: Proceedings of the Sixth Workshop on Natural Language for Artificial Intelligence (NL4AI 2022) co-located with 21th International Conference of the Italian Association for Artificial Intelligence (AI* IA 2022) (2022)"},{"key":"3_CR17","unstructured":"Kingma, D.P., Ba, J.: Adam: a method for stochastic optimization (2017)"},{"key":"3_CR18","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"255","DOI":"10.1007\/978-3-030-35699-6_20","volume-title":"RoboCup 2019: Robot World Cup XXIII","author":"ER Kramer","year":"2019","unstructured":"Kramer, E.R., S\u00e1inz, A.O., Mitrevski, A., Pl\u00f6ger, P.G.: Tell your robot what to do: evaluation of natural language models for robot command processing. In: Chalup, S., Niemueller, T., Suthakorn, J., Williams, M.-A. (eds.) RoboCup 2019. LNCS (LNAI), vol. 11531, pp. 255\u2013267. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-35699-6_20"},{"key":"3_CR19","doi-asserted-by":"crossref","unstructured":"Liu, B., Lane, I.: Attention-based recurrent neural network models for joint intent detection and slot filling. arXiv preprint arXiv:1609.01454 (2016)","DOI":"10.21437\/Interspeech.2016-1352"},{"key":"3_CR20","unstructured":"Martins, P.H., Cust\u00f3dio, L., Ventura, R.: A deep learning approach for understanding natural language commands for mobile service robots. arXiv preprint arXiv:1807.03053 (2018)"},{"key":"3_CR21","doi-asserted-by":"publisher","unstructured":"Masumura, R., Shinohara, Y., Higashinaka, R., Aono, Y.: Adversarial training for multi-task and multi-lingual joint modeling of utterance intent classification. In: Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pp. 633\u2013639. Association for Computational Linguistics, Brussels (2018). https:\/\/doi.org\/10.18653\/v1\/D18-1064, https:\/\/aclanthology.org\/D18-1064","DOI":"10.18653\/v1\/D18-1064"},{"key":"3_CR22","series-title":"Springer Tracts in Advanced Robotics","doi-asserted-by":"publisher","first-page":"403","DOI":"10.1007\/978-3-319-00065-7_28","volume-title":"Experimental Robotics","author":"C Matuszek","year":"2013","unstructured":"Matuszek, C., Herbst, E., Zettlemoyer, L., Fox, D.: Learning to parse natural language commands to a robot control system. In: Desai, J., Dudek, G., Khatib, O., Kumar, V. (eds.) Experimental Robotics. Springer Tracts in Advanced Robotics, vol. 88, pp. 403\u2013415. Springer, Heidelberg (2013). https:\/\/doi.org\/10.1007\/978-3-319-00065-7_28"},{"key":"3_CR23","doi-asserted-by":"crossref","unstructured":"Peng, B., Yao, K.: Recurrent neural networks with external memory for language understanding. arXiv preprint arXiv:1506.00195 (2015)","DOI":"10.1007\/978-3-319-25207-0_3"},{"key":"3_CR24","doi-asserted-by":"crossref","unstructured":"Qin, L., Wei, F., Xie, T., Xu, X., Che, W., Liu, T.: GL-GIN: fast and accurate non-autoregressive model for joint multiple intent detection and slot filling. arXiv preprint arXiv:2106.01925 (2021)","DOI":"10.18653\/v1\/2021.acl-long.15"},{"key":"3_CR25","doi-asserted-by":"crossref","unstructured":"Qin, L., Xu, X., Che, W., Liu, T.: AGIF: an adaptive graph-interactive framework for joint multiple intent detection and slot filling. arXiv preprint arXiv:2004.10087 (2020)","DOI":"10.18653\/v1\/2020.findings-emnlp.163"},{"key":"3_CR26","unstructured":"Sanh, V., Debut, L., Chaumond, J., Wolf, T.: DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter. arXiv preprint arXiv:1910.01108 (2019)"},{"issue":"1","key":"3_CR27","first-page":"61","volume":"18","author":"S Seneff","year":"1992","unstructured":"Seneff, S.: TINA: a natural language system for spoken language applications. Comput. Linguist. 18(1), 61\u201386 (1992)","journal-title":"Comput. Linguist."},{"key":"3_CR28","doi-asserted-by":"crossref","unstructured":"Sun, Z., Yu, H., Song, X., Liu, R., Yang, Y., Zhou, D.: MobileBERT: a compact task-agnostic BERT for resource-limited devices. arXiv preprint arXiv:2004.02984 (2020)","DOI":"10.18653\/v1\/2020.acl-main.195"},{"key":"3_CR29","doi-asserted-by":"publisher","first-page":"144","DOI":"10.3389\/frobt.2019.00144","volume":"6","author":"Y Tada","year":"2020","unstructured":"Tada, Y., Hagiwara, Y., Tanaka, H., Taniguchi, T.: Robust understanding of robot-directed speech commands using sequence to sequence with noise injection. Front. Robot. AI 6, 144 (2020)","journal-title":"Front. Robot. AI"},{"key":"3_CR30","doi-asserted-by":"publisher","unstructured":"Vanzo, A., Croce, D., Bastianelli, E., Basili, R., Nardi, D.: Grounded language interpretation of robotic commands through structured learning. Artif. Intell. 278 (2020). https:\/\/doi.org\/10.1016\/j.artint.2019.103181","DOI":"10.1016\/j.artint.2019.103181"},{"key":"3_CR31","unstructured":"Wu, Y., et al.: Google\u2019s neural machine translation system: bridging the gap between human and machine translation (2016)"},{"key":"3_CR32","doi-asserted-by":"crossref","unstructured":"Yao, K., Zweig, G., Hwang, M.Y., Shi, Y., Yu, D.: Recurrent neural networks for language understanding. In: Interspeech, pp. 2524\u20132528 (2013)","DOI":"10.21437\/Interspeech.2013-569"},{"key":"3_CR33","doi-asserted-by":"crossref","unstructured":"Zheng, Y., Liu, Y., Hansen, J.H.: Intent detection and semantic parsing for navigation dialogue language processing. In: 2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITSC), pp. 1\u20136. IEEE (2017)","DOI":"10.1109\/ITSC.2017.8317620"}],"container-title":["Lecture Notes in Computer Science","RoboCup 2023: Robot World Cup XXVI"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-55015-7_3","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,14]],"date-time":"2024-11-14T07:51:56Z","timestamp":1731570716000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-55015-7_3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031550140","9783031550157"],"references-count":33,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-55015-7_3","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"14 March 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"RoboCup","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Robot World Cup","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Bordeaux","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"France","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4 July 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10 July 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"robocup2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/2023.robocup.org\/en\/home\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"easychair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"59","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"36","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"61% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}